Add dataset loading script

synthtiger.py

@@ -0,0 +1,221 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""SynthTiger synthetic OCR dataset in huggingface format.
+
+https://github.com/clovaai/synthtiger
+https://drive.google.com/drive/folders/1faHxo6gVeUmmFKJf8dxFZf_yRjamUL96
+synthtiger_v1.1.zip (38G) (md5: b2757a7e2b5040b14ed64c473533b592)
+
+Unpacked dataset structure:
+```
+gt.txt
+images/
+    0/
+        0.jpg
+        1.jpg
+        ...
+        9998.jpg
+        9999.jpg
+    1/
+    ...
+    998/
+        ...
+    999/
+        9990000.jpg
+        9990001.jpg
+        ...
+        9999998.jpg
+        9999999.jpg
+```
+
+gt.txt format (tab delimited):
+```
+images/0/0.jpg	10
+images/0/1.jpg	date:
+...
+images/999/9999998.jpg	STUFFIER
+images/999/9999999.jpg	Re:
+```"""
+import os
+import shutil
+
+from PIL import Image
+
+import datasets
+
+
+_CITATION = """\
+@inproceedings{yim2021synthtiger,
+  title={Synthtiger: Synthetic text image generator towards better text recognition models},
+  author={Yim, Moonbin and Kim, Yoonsik and Cho, Han-Cheol and Park, Sungrae},
+  booktitle={International Conference on Document Analysis and Recognition},
+  pages={109--124},
+  year={2021},
+  organization={Springer}
+}
+"""
+
+_DESCRIPTION = """\
+A synthetic scene text OCR dataset derived from the
+[SynthTIGER](https://github.com/clovaai/synthtiger) generator.
+"""
+
+_HOMEPAGE = "https://github.com/clovaai/synthtiger"
+
+_LICENSE = """\
+SynthTIGER
+Copyright (c) 2021-present NAVER Corp.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.
+"""
+
+_FOLDER_URL = "https://drive.google.com/drive/folders/18wjIad7_R9AXqXlQ4bhgOxMZY_8XRCdh?usp=sharing"
+_PART_URLS = {
+    "synthtiger_v1.1.zip.00": "https://drive.google.com/file/d/1ELxTy95sAFQ1ZD81QqS_dbMBnqi6N7aR/view?usp=sharing",
+    "synthtiger_v1.1.zip.01": "https://drive.google.com/file/d/1mf9rNBlAVC_xMRUkXmjJSyIBhVgPstPR/view?usp=sharing",
+    "synthtiger_v1.1.zip.02": "https://drive.google.com/file/d/1AN0d96JaCZRq37UP3ZHTnEjl-1YwXajR/view?usp=sharing",
+    "synthtiger_v1.1.zip.03": "https://drive.google.com/file/d/1WCj-S7GXDlRpLEcHRdnIyjVZTcoY1zJU/view?usp=sharing",
+    "synthtiger_v1.1.zip.04": "https://drive.google.com/file/d/1iWOh-dUUSTDOD9jYbSSe5Iq1qiDyYtOg/view?usp=sharing",
+    "synthtiger_v1.1.zip.05": "https://drive.google.com/file/d/1QtEoZpNsTCUtq4DuZ5IwdJpuFpeNJCXK/view?usp=sharing",
+    "synthtiger_v1.1.zip.06": "https://drive.google.com/file/d/1lTlRRxqkhkgA3CMJ5cSz2-6n_F07KnJ-/view?usp=sharing",
+    "synthtiger_v1.1.zip.07": "https://drive.google.com/file/d/1iERfjCHzX9_i-WchYazaK9mF6--41r6b/view?usp=sharing",
+    "synthtiger_v1.1.zip.08": "https://drive.google.com/file/d/1pxhGbTP3tDMh8cJTz-d7A-gq4_nWSZIO/view?usp=sharing",
+    "synthtiger_v1.1.zip.09": "https://drive.google.com/file/d/1WJ-QrHsp6joWAU5JVs3TgpMCvz-E4YKq/view?usp=sharing",
+    "synthtiger_v1.1.zip.10": "https://drive.google.com/file/d/1Pp3TRa60oUDHLIhN0oQ_y4SukXxfIjcw/view?usp=sharing",
+}
+_ARCHIVE_ROOT = "synthtiger_v1.1"
+
+
+def _get_google_drive_url(url):
+    """Re-format the "Get link" version of a Google Drive URL."""
+    base_url = "https://drive.google.com/uc?id="
+    split_url = url.split("/")
+    return base_url + split_url[5]
+
+
+class Synthtiger(datasets.GeneratorBasedBuilder):
+    """A synthtetic scene text OCR dataset generated by SynthTIGER."""
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        """Define dataset metadata and feature types."""
+        features = datasets.Features(
+            {
+                "image": datasets.Image(),
+                "transcript": datasets.Value("string"),
+                "height": datasets.Value("uint32"),
+                "width": datasets.Value("uint32"),
+                "aspect_ratio": datasets.Value("float32"),
+                "script": datasets.Value("string"),
+                "lang": datasets.Value("string"),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=("image", "transcript"),
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Build split metadata and fetch data if needed."""
+        folder_url = _FOLDER_URL
+        part_urls = {k: _get_google_drive_url(v) for k, v in _PART_URLS.items()}
+
+        def custom_download(src_url: str, dest_path: str):
+            """Internal utility to download and combine archive parts.
+
+            As of October 23, 2021, the SynthTIGER dataset v1.1 is distributed
+            via Google Drive. It is a ~38Gb zip file split into 11 parts of
+            ~3.5Gb each with the `split` utility. This means that the parts
+            are not usable archives on their own, they must be concatenated
+            back into the whole zip file before any of the contents can be
+            extracted.
+
+            This inner function provides a closure around the `dl_manager` and
+            `part_urls` variables so that the download manager's custom
+            download function can track and cache the download of the parts as
+            well as the concatenated version. This makes it easier to re-start
+            an interrupted download of the parts at the cost of disk space.
+
+            The `src_url` is chosen to be the viewable folder url for Google
+            Drive, but it serves no purpose except to be a hashable string
+            that allows the concatenated archive to be cached.
+
+            The parts of the download will not be cleaned up. This would be
+            easy to add if needed, since the paths are known, but keeping them
+            makes the download manager's stats more accurate. The parts should
+            not be needed once the full archive has been cached and can be
+            deleted manually.
+            """
+            downloaded_part_paths = dl_manager.download(part_urls)
+            with open(dest_path, "wb") as concatenated_file:
+                for name, path in downloaded_part_paths.items():
+                    with open(path, "rb") as part_file:
+                        shutil.copyfileobj(part_file, concatenated_file)
+            return dest_path
+
+        archive_path = dl_manager.download_custom(folder_url, custom_download)
+        extracted_dir = dl_manager.extract(archive_path, num_proc=1)
+        data_dir = os.path.join(extracted_dir, _ARCHIVE_ROOT)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data_dir": data_dir,
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_dir, split):
+        """Iterate over dataset images and annotations."""
+        gt_path = os.path.join(data_dir, "gt.txt")
+        with open(gt_path, encoding="utf-8") as gt_file:
+            for key, line in enumerate(gt_file):
+                rel_path, transcript = line.strip().split("\t")
+                image_path = os.path.join(data_dir, rel_path)
+                image = Image.open(image_path)
+                width, height = image.size
+                aspect_ratio = width / height
+                yield key, {
+                    "image": image,
+                    "transcript": transcript,
+                    "height": height,
+                    "width": width,
+                    "aspect_ratio": aspect_ratio,
+                    "script": "Latn",
+                    "lang": "en",
+                }